def list_vms(host=None):
"""
make a list of vms and expand out their fixed_ip and floating ips sensibly
"""
flags.parse_args([])
my_instances = []
if host is None:
instances = db.instance_get_all(context.get_admin_context())
else:
instances = db.instance_get_all_by_host(
context.get_admin_context(), host)
for instance in instances:
my_inst = {}
my_inst = dict(instance).copy()
for (k,v) in my_inst.items():
try:
json.encoder(v)
except TypeError, e:
v = str(v)
my_inst[k] = v
ec2_id = db.get_ec2_instance_id_by_uuid(context.get_admin_context(), instance.uuid)
ec2_id = 'i-' + hex(int(ec2_id)).replace('0x', '').zfill(8)
my_inst['ec2_id'] = ec2_id
try:
fixed_ips = db.fixed_ip_get_by_instance(context.get_admin_context(), instance.uuid)
except:
pass
my_inst['fixed_ips'] = [ ip.address for ip in fixed_ips ]
my_inst['floating_ips'] = []
for ip in fixed_ips:
my_inst['floating_ips'].extend([ f_ip.address for f_ip in db.floating_ip_get_by_fixed_address(context.get_admin_context(), ip.address)])
my_instances.append(my_inst)
def get(self, command):
if command == 'playlists':
playlists = None
try:
playlists = pickle.load(open('cache/playlists.p', 'rb+'))
except:
with self.sp.current_user_playlists() as reply:
print(reply)
playlists = json.encoder(reply)
pickle.dump(playlists, open('cache/playlists.p', 'wb+'))
return playlists
elif command == 'token':
try:
return {"token": self.token, "refresh": 'None'}
except:
return {"token": "none", "refresh": "none"}
elif command == 'Search':
state = json.loads(request.data)
self.DB.Search(state['Query'], state['ReturnAmt'], state['Type'])
else:
return {"command": "invalid"}
def make_book_json(self,
ISBN,
Title,
Pub_Year,
Pub_Name,
Pub_City,
Pub_URL,
Authors=[],
Notes=[],
Edition=1,
Language='English'):
notes_list = []
for note in Notes:
notes_list.append({"Text": "{0}".format(note)})
book_dict = {
"ISBN": ISBN,
"Title": Title,
"Pub_Year": Pub_Year,
"Edition": Edition,
"Language": Language,
"Authors": self.make_authors_dict_list(Authors),
"Publisher": {
"Name": Pub_Name,
"City": Pub_City,
"URL": Pub_URL,
},
"Notes": notes_list,
}
return encoder().encode(book_dict)
def list_vms(host=None):
"""
make a list of vms and expand out their fixed_ip and floating ips sensibly
"""
flags.parse_args([])
my_instances = []
if host is None:
instances = db.instance_get_all(context.get_admin_context())
else:
instances = db.instance_get_all_by_host(context.get_admin_context(),
host)
for instance in instances:
my_inst = {}
my_inst = dict(instance).copy()
for (k, v) in my_inst.items():
try:
json.encoder(v)
except TypeError, e:
v = str(v)
my_inst[k] = v
ec2_id = db.get_ec2_instance_id_by_uuid(context.get_admin_context(),
instance.uuid)
ec2_id = 'i-' + hex(int(ec2_id)).replace('0x', '').zfill(8)
my_inst['ec2_id'] = ec2_id
try:
fixed_ips = db.fixed_ip_get_by_instance(
context.get_admin_context(), instance.uuid)
except:
pass
my_inst['fixed_ips'] = [ip.address for ip in fixed_ips]
my_inst['floating_ips'] = []
for ip in fixed_ips:
my_inst['floating_ips'].extend([
f_ip.address for f_ip in db.floating_ip_get_by_fixed_address(
context.get_admin_context(), ip.address)
])
my_instances.append(my_inst)
def post_search_query():
input_string = "https://upload.wikimedia.org/wikipedia/commons/7/71/2010-kodiak-bear-1.jpg"
# check if string is url
if re.search("(?:http\:|https\:)?\/\/.*\.(?:png|jpg)", input_string):
input_string = string_from_image(input_string)
# validate input
if not input_string or len(input_string) > max_query_lengh:
return (json.encoder({
"success": False,
"message": "query length too long"
}))
# get category
category = categorize_string(input_string)
print(category)
# get wiki data
wiki_data = komila.create_maps(input_string)
if category == animal:
wolfram_data = aaron.process_animal(input_string)
summary = anthony.summarize_animals(wiki_data, wolfram_data)
elif category == person:
wolfram_data = aaron.process_person(input_string)
summary = anthony.summarize_person(wiki_data, wolfram_data)
elif category == planet:
wolfram_data = aaron.process_planet(input_string)
summary = anthony.summarize_planets(wiki_data, wolfram_data)
elif category == cities:
wolfram_data = aaron.process_cities(input_string)
summary = anthony.summarize_cities(wiki_data, wolfram_data)
else:
return json.dumps({
"success": False,
"message": "could not find category"
})
if not summary["success"]:
return json.dumps({
"success": False,
"message": "failure in summarize"
})
del summary["success"]
return json.dumps(summary)
def build_transformer(
vocab_size: int,
input_length: int = 32,
model_name: str = "cl-tohoku/bert-base-japanese",
hopping_num: int = 6,
head_num: int = 8,
hidden_dim: int = 512,
dropout_rate: float = 0.1,
encoder_output_dim: int = 768,
target_length: int = 64,
) -> tf.keras.models.Model:
input_shape = (input_length, )
input_ids = tf.keras.layers.Input(input_shape,
dtype=tf.int32,
name="input_ids")
input_attention_mask = tf.keras.layers.Input(input_shape,
dtype=tf.int32,
name="input_attention_mask")
encoder = TFBertModel.from_pretrained(
model_name) #, output_attentions=True)
encoder.trainable = False
encoder_output = encoder(
input_ids,
attention_mask=input_attention_mask,
)
target_ids = tf.keras.layers.Input((target_length, ),
dtype=tf.int32,
name="target_ids")
decoder = Decoder(
vocab_size=vocab_size,
hopping_num=hopping_num,
head_num=head_num,
hidden_dim=hidden_dim,
dropout_rate=dropout_rate,
)
output = decoder(
input=target_ids,
encoder_output=encoder_output[0],
source_mask=input_attention_mask,
)
model = tf.keras.Model(
inputs=[input_ids, input_attention_mask, target_ids], outputs=[output])
return model
country = string[1].split('.')[0]
for i,t in enumerate(b):
string = t[0].split('//')
if len(string) > 1:
country = string[1].split('.')[0]
if country != "www":
b[i][0] = country
b
d = dict(b)
d
b.index(['http://www.digikey.com': u'http://www.digikey.com/classic/Ordering/AddPart.aspx?site=us&lang=en',
b.index(['http://www.digikey.com', u'http://www.digikey.com/classic/Ordering/AddPart.aspx?site=us&lang=en'])
b[73][0] = "us"
url_enc = "redirectInfo=%7b%24%24type%3a%22RedirectInfo%22%2cc_PrevRedirect%3anull%2cServerEventID%3a%2251b92548-35a8-0000-b7cf-9c0017dab884%22%2cTo%3a%22wFF5snc1zRvwEMfhXlllqtG%5c%5cx2bo28pCpKLqQ37LeUfz4Y%5c%5cx3d%22%2cFrom%3a%22m0%5c%5cx2f0vd1Lrg58oSlZaJ3gDO7srlmm9bKKycrrsCwadgYJyXurtSPC%5c%5cx2fgeLBi2aa%5c%5cx2bbbj2BuWr9jGz%5c%5cx2bRxIdrRfAg1%5c%5cx2bApmlw6DMObqy1uvL8xBF0dpTgdOC380u3trJnBo0WLdxWOS8FdIki%5c%5cx2bBRjLUHnzMpGdgOkyAmynLNCLZ%5c%5cx2bP2cSi2HQpxkC8tI1Yk0csUFWcC7kN%5c%5cx2ftvZfvAFTdXymK7cqNw%5c%5cx3d%5c%5cx3d%22%2cc_ServerTime%3a94%2cStartDateTicks%3a1371139153298%2cEndDateTicks%3a1371139153392%2cc_Summary%3anull%2cT9%3a-1%2cTime%3a%222013-06-13T15%3a59%3a13.298%22%7d; ASP.NET_SessionId=hgaqk2i3cbryqeuiaposf4n5; CARTCOOKIEUUID=1cfd6a60-3c08-43b2-ac53-3b717b96b875; preferences=ps=gb&pl=en-GB&pc_gb=GBP; _csm_ux_data"
d = dict(b)
d
d[us]
d["us"]
b.index(['http://www.digikey.com', u'http://www.digikey.com/classic/Ordering/AddPart.aspx?site=us&lang=en'])
a[73]
a[77]
b[77][0] = "int"
d = dict(b)
d
import json
json.encoder(d)
json.encoder.encode_basestring(d)
with open "digikey_international.json", "w") as outfile:
json.dump(d, outfile)
with open ("digikey_international.json", "w") as outfile:
json.dump(d, outfile)
def hello_class():
json.encoder(Person('121', '1231231'))
return json.encoder(Person('121', '1231231'))